Hierarchical virtual screening of the dual MMP-2/HDAC-6 inhibitors from natural products based on pharmacophore models and molecular docking

Pharmacophore-based virtual screening, molecular docking and molecular dynamics simulation for identification of potential ERK inhibitors

As the downstream component of the mitogen-activated protein kinases (MAPK) pathway, the extracellular signal-regulated kinase (ERK) is responsible for phosphorylating a broad range of substrates in cell proliferation, differentiation, and survival. Direct targeting the ERK proteins by the piperidinopyrimidine urea-based inhibitors has been demonstrated to be an effective way to block the MAPK signaling pathway in inhibiting tumor growth. In order to discover better inhibitors, a computer-aided drug design (CADD) approach was employed to reveal the pharmacological characteristics and mechanisms of action. The pharmacophore model was generated on the basis of the compounds with eight features, i.e., four hydrogen bond acceptor atoms, one hydrogen bond donor atom, and three hydrophobic centers. A total of 14 hit compounds were obtained through virtual screening. Two potential inhibitors, namely VS01 and VS02, have been identified by molecular docking and molecular dynamics simulations. Both compounds are capable of attaching to the ERK pocket precisely. The binding free energies of VS01 and VS02 are about 15 kJ/mol and 4 kJ/mol stronger than that of the clinic Ulixertinib because of the characteristic hydrogen bonding, electrostatic, and hydrophilic interactions. The present theoretical investigations shed new light on the rational design of the potential ERK inhibitors to stimulate further experimental tests.Communicated by Ramaswamy H. Sarma.

Unveiling Arformoterol as a potent LSD1 inhibitor for breast cancer treatment: A comprehensive study integrating 3D-QSAR pharmacophore modeling, molecular docking, molecular dynamics simulations and in vitro assays

Lysine Specific Demethylase 1 (LSD1) has been identified as a chromatin-modifying enzyme implicated in various cancer pathogeneses, highlighting the potential for novel epigenetic cancer treatments through the development of effective inhibitors. We employed 3D-QSAR pharmacophore modeling, molecular docking, and molecular dynamics simulations to identify a promising drug candidate for LSD1 inhibition. RMSD, RMSF, H-bond, and DSSP analysis demonstrated that ZINC02599970 (Arformoterol) and ZINC13453966 exhibited the highest LSD1 inhibitory potential. Experimental validation using MCF-7 and MDA-MB-231 cell lines revealed that Arformoterol displayed potent antiproliferative activity with IC50 values of 12.30 ± 1.48 μM and 19.69 ± 1.15 μM respectively. In contrast, the IC50 values obtained for the control (tranylcypromine) in exposure to MCF-7 and MDA-MB-231 cells were 104.6 ± 1.69 μM and 77 ± 0.67 μM, respectively. Arformoterol demonstrated greater LSD1 inhibitory potency in MCF-7 cells compared to MDA-MB-231 cells. Also, the expression of genes involved in chromatin rearrangement (LSD1), angiogenesis (VEGF1), cell migration (RORα), signal transduction (S100A8), apoptosis, and cell cycle (p53) were investigated. Arformoterol enhanced apoptosis and induced cell cycle arrest at the G2/M phase, both in MCF-7 and MDA-MB-231 cancer cells. Based on our findings, we propose that Arformoterol represents a promising candidate for breast cancer treatment, owing to its potent LSD1 inhibitory activity.

Lansoprazole as a potent HDAC2 inhibitor for treatment of colorectal cancer: An in-silico analysis and experimental validation

BACKGROUND

Histone deacetylase 2 (HDAC2), belonging to the class I HDAC family, holds significant therapeutic potential as a crucial target for diverse cancer types. As key players in the realm of epigenetic regulatory enzymes, histone deacetylases (HDACs) are intricately involved in the onset and progression of cancer. Consequently, pursuing isoform-specific inhibitors targeting histone deacetylases (HDACs) has garnered substantial interest in both biological and medical circles. The objective of the present investigation was to employ a drug repurposing approach to discover novel and potent HDAC2 inhibitors.

MATERIALS AND METHODS

In this study, our protocol is presented on virtual screening to identify novel potential HDAC2 inhibitors through 3D-QSAR, molecular docking, pharmacophore modeling, and molecular dynamics (MD) simulation. Afterward, In-vitro assays were employed to evaluate the cytotoxicity, apoptosis, and migration of HCT-116 cell lines under treatment of hit compound and valproic acid as a control inhibitor. The expression levels of HDAC2, TP53, BCL2, and BAX were evaluated by QRT-PCR.

RESULTS

RMSD, RMSF, H-bond, and DSSP analysis results confirmed that among bioinformatically selected compounds, lansoprazole exhibited the highest HDAC2 inhibitory potential. Experimental validation revealed that lansoprazole displayed significant antiproliferative activity. The determined IC50 value was 400 ± 2.36 μM. Furthermore, the apoptotic cells ratio concentration-dependently increased under Lansoprazole treatment. Results of the Scratch assay indicated that lansoprazole led to decreasing the migration of CRC cells. Finally, under Lansoprazole treatment the expression level of BCL2 and HDAC2 decreased and BAX and TP53 increased.

CONCLUSION

Taking together the results of the current study indicated that Lansoprazole as a novel HDAC2 inhibitor, could be used as a potential therapeutic agent for the treatment of CRC. Although, further experimental studies should be performed before using this compound in the clinic.

Pharmacophore-based virtual screening of ZINC database, molecular modeling and designing new derivatives as potential HDAC6 inhibitors

To date, many HDAC6 inhibitors have been identified and developed but none is clinically approved as of now. Through this study, we aim to obtain novel HDAC6 selective inhibitors and provide new insights into the detailed structural design of potential HDAC6 inhibitors. A HypoGen-based 3D QSAR HDAC6 pharmacophore was built and used as a query model to screen approximately 8 million ZINC database compounds. First, the ZINC Database was filtered using ADMET, followed by pharmacophore-based library screening. Using fit value and estimated activity cutoffs, a final set of 54 ZINC hits was obtained that were further investigated using molecular docking with the crystal structure of human histone deacetylase 6 catalytic domain 2 in complex with Trichostatin A (PDB ID: 5EDU). Through detailed in silico screening of the ZINC database, we shortlisted three hits as the lead molecules for designing novel HDAC6 inhibitors with better efficacy. Docking with 5EDU, followed by ADMET and TOPKAT analysis of modified ZINC hits provided 9 novel potential HDAC6 inhibitors that possess better docking scores and 2D interactions as compared to the control ZINC hit molecules. Finally, a 50 ns MD analysis run followed by Protein-Ligand Interaction Energy (PLIE) analysis of the top scored hits provided a novel molecule N1 that showed promisingly similar results to that of Ricolinostat (a known HDAC6 inhibitor). The comparable result of the designed hits to established HDAC6 inhibitors suggests that these compounds might prove to be successful HDAC6 inhibitors in future. Designed novel hits that might act as good HDAC6 inhibitors derived from ZINC database using combined molecular docking and modeling approaches.

Identification of novel leads as potent inhibitors of HDAC3 using ligand-based pharmacophore modeling and MD simulation

In the landscape of epigenetic regulation, histone deacetylase 3 (HDAC3) has emerged as a prominent therapeutic target for the design and development of candidate drugs against various types of cancers and other human disorders. Herein, we have performed ligand-based pharmacophore modeling, virtual screening, molecular docking, and MD simulations to design potent and selective inhibitors against HDAC3. The predicted best pharmacophore model ‘Hypo 1’ showed excellent correlation (R² = 0.994), lowest RMSD (0.373), lowest total cost value (102.519), and highest cost difference (124.08). Hypo 1 consists of four salient pharmacophore features viz. one hydrogen bond acceptor (HBA), one ring aromatic (RA), and two hydrophobic (HYP). Hypo 1 was validated by Fischer's randomization with a 95% of confidence level and the external test set of 60 compounds with a good correlation coefficient (R² = 0.970). The virtual screening of chemical databases, drug-like properties calculations followed by molecular docking resulted in identifying 22 representative hit compounds. Performed 50 ns of MD simulations on top three hits were retained the salient π-stacking, Zn²⁺ coordination, hydrogen bonding, and hydrophobic interactions with catalytic residues from the active site pocket of HDAC3. Total binding energy calculated by MM-PBSA showed that the Hit 1 and Hit 2 formed stable complexes with HDAC3 as compared to reference TSA. Further, the PLIP analysis showed a close resemblance between the salient pharmacophore features of Hypo 1 and the presence of molecular interactions in co-crystallized FDA-approved drugs. We conclude that the screened hit compounds may act as potent inhibitors of HDAC3 and further preclinical and clinical studies may pave the way for developing them as effective therapeutic agents for the treatment of different cancers and neurodegenerative disorders.

Cannabinoid Receptor Subtype 2 (CB2R) in a Multitarget Approach: Perspective of an Innovative Strategy in Cancer and Neurodegeneration

The cannabinoid receptor subtype 2 (CB2R) represents an interesting and new therapeutic target for its involvement in the first steps of neurodegeneration as well as in cancer onset and progression. Several studies, focused on different types of tumors, report a promising anticancer activity induced by CB2R agonists due to their ability to reduce inflammation and cell proliferation. Moreover, in neuroinflammation, the stimulation of CB2R, overexpressed in microglial cells, exerts beneficial effects in neurodegenerative disorders. With the aim to overcome current treatment limitations, new drugs can be developed by specifically modulating, together with CB2R, other targets involved in such multifactorial disorders. Building on successful case studies of already developed multitarget strategies involving CB2R, in this Perspective we aim at prompting the scientific community to consider new promising target associations involving HDACs (histone deacetylases) and σ receptors by employing modern approaches based on molecular hybridization, computational polypharmacology, and machine learning algorithms.

Dual inhibitors of histone deacetylases and other cancer-related targets: A pharmacological perspective

Epigenetic enzymes histone deacetylases (HDACs) are clinically validated anticancer drug targets which have been studied intensively in the past few decades. Although several drugs have been approved in this field, they are still limited to a subset of hematological malignancies (in particular T-cell lymphomas), with therapeutic potential not fully realized and the drug-resistance occurred after a certain period of use. To maximize the therapeutic potential of these classes of anticancer drugs, and to extend their application to solid tumors, numerous combination therapies containing an HDACi and an anticancer agent from other mechanisms are currently ongoing in clinical trials. Recently, dual targeting strategy comprising the HDACs component has emerged as an alternative approach for combination therapies. In this perspective, we intend to gather all HDACs-containing dual inhibitors related to cancer therapy published in literature since 2015, classify them into five categories based on targets' biological functions, and discuss the rationale why dual acting agents should work better than combinatorial therapies using two separate drugs. The article discusses the pharmacological aspects of these dual inhibitors, including in vitro biological activities, pharmacokinetic studies, in vivo efficacy studies, as well as available clinical trials. The review of the current status and advances should provide better analysis for future opportunities and challenges of this field.

Paradigm shift of "classical" HDAC inhibitors to "hybrid" HDAC inhibitors in therapeutic interventions

'Epigenetic' regulation of genes via post-translational modulation of proteins is the current mainstay approach for the disease therapies, particularly explored in the Histone Deacetylase (HDAC) class of enzymes. Mainly sight saw in cancer chemotherapeutics, HDAC inhibitors have also found a promising role in other diseases (neurodegenerative disorders, cardiovascular diseases, and viral infections) and successfully entered in various combination therapies (pre-clinical/clinical stages). The prevalent flexibility in the structural design of HDAC inhibitors makes them easily tuneable to merge with other pharmacophore modules for generating multi-targeted single hybrids as a novel tactic to overcome drawbacks of polypharmacy. Herein, we reviewed the putative role of prevalent HDAC hybrids inhibitors in the current and prospective stage as a translational approach to overcome the limitations of the existing conventional drug candidates (parent molecule) when used either alone (drug resistance, solubility issues, adverse side effects, selectivity profile) or in combination (pharmacokinetic interactions, patient compliance) for treating various diseases.

Dual-Target Inhibitors Based on HDACs: Novel Antitumor Agents for Cancer Therapy

Histone deacetylases (HDACs) play an important role in regulating target gene expression. They have been highlighted as a novel category of anticancer targets, and their inhibition can induce apoptosis, differentiation, and growth arrest in cancer cells. In view of the fact that HDAC inhibitors and other antitumor agents, such as BET inhibitors, topoisomerase inhibitors, and RTK pathway inhibitors, exert a synergistic effect on cellular processes in cancer cells, the combined inhibition of two targets is regarded as a rational strategy to improve the effectiveness of these single-target drugs for cancer treatment. In this review, we discuss the theoretical basis for designing HDAC-involved dual-target drugs and provide insight into the structure-activity relationships of these dual-target agents.

Identification of HDAC6 selective inhibitors: pharmacophore based virtual screening, molecular docking and molecular dynamics simulation

HDAC6 regulates the expression and activity of various tumor-related proteins, but currently there is no selective inhibitor targeting HDAC6 for clinical application. In order to discover novel HDAC6 inhibitors, virtual screening methods comprised of pharmacophore based virtual screening, molecular docking and molecular dynamics (MD) simulations were employed. 15 molecules were obtained after virtual screening. After in vitro bioassays, two of the hits showed inhibition activity against HDAC6, among which the inhibition activity of G1 to HDAC6 reached 81% at concentration of 20 μM. In addition, the inhibitory activity against HDAC1 and HDAC10 demonstrated that G1 and G10 were highly selective to HDAC6. The analysis of the binding modes of G1 and G10 provides a reference for further development of highly active HDAC6 inhibitors. Communicated by Ramaswamy H. Sarma.

Computational investigation reveals Picrasidine C as selective PPARα lead: binding pattern, selectivity mechanism and ADME/tox profile

Natural products and their derivatives have been recognized as an important source of therapeutic agents for many years. Previously we isolated a dimeric β-carboline-type alkaloid Picrasidine C from the root of Picrasma quassioides as subtype-selective peroxisome proliferator-activated receptor α (PPARα) agonist. In order to modify this natural product for better affinity and druggability, we investigated a series of properties exhibited by Picrasidine C, such as its binding mode with PPARα, the selectivity mechanism over PPARγ, as well as ADME/Tox profile through computational methods including sequence alignment, molecular docking, pharmacophore modeling and molecular dynamics simulations. The detailed information of binding pattern and affinity for Picrasidine C elucidated here will be valuable for chemical modification. Besides, the steric hindrance of residue Phe363 in PPARγ pocket was speculated as the main isoform selectivity mechanism for Picrasidine C, which would be helpful for the design of selective derivatives. ADME/Tox prediction was conducted to avoid potential undesirable pharmacokinetic properties for reducing the risk of failure. Finally, novel skeletons were derived from lead compound by core hopping method, validated through molecular dynamic simulations and MM-GBSA calculation. In short, the information obtained from computational strategy would be valuable for us to find more potent, safe and selective PPARα agonists during structural optimization.

Recent insights into natural product inhibitors of matrix metalloproteinases

Members of the matrix metalloproteinase (MMP) family have biological functions that are central to human health and disease, and MMP inhibitors have been investigated for the treatment of cardiovascular disease, cancer and neurodegenerative disorders. The outcomes of initial clinical trials with the first generation of MMP inhibitors proved disappointing. However, our growing understanding of the complexities of the MMP function in disease, and an increased understanding of MMP protein architecture and control of activity now provide new opportunities and avenues to develop MMP-focused therapies. Natural products that affect MMP activities have been of strong interest as templates for drug discovery, and for their use as chemical tools to help delineate the roles of MMPs that still remain to be defined. Herein, we highlight the most recent discoveries of structurally diverse natural product inhibitors to these proteases.

In silico identification of natural products with anticancer activity using a chemo-structural database of Brazilian biodiversity

Cancer is one of the leading causes of death worldwide, and the number of patients has only increased each year, despite the considerable efforts and investments in scientific research. Since natural products (NPs) may serve as suitable sources for drug development, the cytotoxicity against cancer cells of 2221 compounds from the Nuclei of Bioassays, Ecophysiology, and Biosynthesis of Natural Products Database (NuBBE_DB) was predicted using CDRUG algorithm. Molecular modeling, chemoinformatics, and chemometric tools were then used to analyze the structural and physicochemical properties of these compounds. We compared the positive NPs with FDA-approved anticancer drugs and predicted the molecular targets involved in the anticancer activity. In the present study, 46 families comprising potential anticancer compounds and at least 19 molecular targets involved in oncogenesis. To the best of our knowledge, this is the first large-scale study conducted to evaluate the potentiality of NPs sourced from Brazilian biodiversity as anticancer agents, using in silico approaches. Our results provided interesting insights about the mechanism of action of these compounds, and also suggested that their structural diversity may aid structure-based optimization strategies for developing novel drugs for cancer therapy.

Structure-based design of selective histone deacetylase 6 zinc binding groups

The binding site of the second catalytic domain of human histone deacetylase 6 (HDAC6 CDII) has structural features that differ from the other human orthologues, being also mainly responsible for the overall enzymatic activity of this isoform. Aiming to identify new fragments as a possible novel selective zinc binding group (ZBG) for HDAC6 CDII, two fragment libraries were designed: one library consisting of known chelators and a second one using the fragments of the ZINC15 database. The most promising fragments identified in a structure-based virtual screening of designed libraries were further evaluated through molecular docking and molecular dynamics simulations. An interesting benzimidazole fragment was selected from the in silico studies and presented as potential zing binding group for the development of novel HDAC6 selective inhibitors.Communicated by Ramaswamy H. Sarma.

Structural exploration of tetrahydroisoquinoline derivatives as HDAC8 inhibitors through multi-QSAR modeling study

Histone deacetylase 8 (HDAC8) is one of the crucial HDACs responsible for influencing the epigenetic functions of the body. Overexpression of HDAC8 is found to be involved in numerous disease conditions such as tumorigenesis, cell proliferation, cancer, viral infections, neuronal disorders and other epigenetic diseases. Therefore, inhibition of HDAC8 is a primary method to combat these diseases. In this article, a multi-QSAR modeling study on tetrahydroisoquinoline derivatives was conducted to identify important contributions of the structural features of these compounds toward HDAC8 inhibition. All these QSAR modeling techniques were individually validated and justified the observations of each other. The results implied that the tetrahydroisoquinoline moiety may be effective as a cap group than as a linker moiety for HDAC8 inhibition. Different substitutions at the tetrahydroisoquinoline scaffold were also found to be crucial in modulating HDAC8 inhibition.Communicated by Ramaswamy H. Sarma.

Combined pharmacophore modeling, 3D-QSAR and docking studies to identify novel HDAC inhibitors using drug repurposing

Histone deacetylases (HDACs), a critical family of epigenetic enzymes, has emerged as a promising target for antitumor drugs. Here, we describe our protocol of virtual screening in identification of novel potential HDAC inhibitors through pharmacophore modeling, 3D-QSAR, molecular docking and molecular dynamics (MD) simulation. Considering the limitation of current virtual screening works, drug repurposing strategy was applied to discover druggable HDAC inhibitor. The ligand-based pharmacophore and 3D-QSAR models were established, and their reliability was validated by different methods. Then, the DrugBank database was screened, followed by molecular docking. MD simulation (100 ns) was performed to further study the stability of ligand binding modes. Finally, results indicated the hit DB03889 with high in silico inhibitory potency was suitable for further experimental analysis.Communicated by Ramaswamy H. Sarma.